Amino acids are among the most important biochemical substances in nature. Of particular interest are the 20 natural or primary protein amino acids, which are alanine, cysteine, aspartic acid, glutamic acid, phenylalanine, glycine, histidine, isoleucine, lysine, leucine, methionine, asparagine, proline, glutamine, arginine, serine, threonine, valine, tryptophan, and tyrosine. In addition to being the building blocks of all proteins, the 20 natural amino acids play important roles in metabolism
Thus, amino acid analysis is of broad interest, having applications in virtually every aspect of biochemical research, biotechnology (agriculture, medicine), clinical medicine, food technology and large-scale proteome projects. Amino acid analysis is applied to a vast range of samples of differing complexity, including simple purified peptides and proteins in analytical biochemistry and pharmacology; complex biological samples from plants, animals, and microbes; body fluids in clinical chemistry; human and animal foods and nutritional supplements. In addition, amino acid analysis is crucial to protein chemistry and is used for routine quality control and screening of biological samples.
Research in protein chemistry is dependent upon the analysis of amino acids. Amino acid analysis is used not only to identify a protein, but is the only reliable method for determining the molar concentration of a protein. For example, amino acid analysis may be used to determine the protein-protein interaction ratios in various complexes. When coupled with exopeptidase digestions, amino acid analysis can be used for protein end group (N-terminal and C-terminal) amino acid compositional and amino acid sequence analysis. Such protein end group amino acid analysis can be used to identify proteins and provide important information about the primary structure of proteins. It is especially important to determine the N- and C-terminal sequence “tag” (short N- or C-terminal amino acid sequence) of intact proteins. This information is used to verify the start and stop point of a protein or gene, and is important in allowing PCR cloning of a complete gene, as well as identifying limited proteolysis.
In large-scale proteome projects, where the aim is to characterize all proteins expressed by the genome, there is great interest in amino acid analysis for the purpose of protein identification and characterization. For example, amino acid analysis is used to identify proteins separated by two-dimensional polyacrylamide gel electrophoresis where thousands of proteins are separated in a single experiment.
Further, with the ever-increasing use of proteins as therapeutics, amino acid analysis finds wide applications in drug research and development. In the pharmaceutical industry, amino acid analysis is used to quantitate a protein or peptide of interest including drugs intended for human use, in quality control testing of protein based drugs, and in protein identification and analysis.
Amino acid analysis is also routinely used in quality control analysis of amino acid containing products including proteins, peptides, pharmaceuticals, industrial enzymes, nutritional supplements and foods where amino acids are both important nutrients and indicators of protein composition. In clinical medicine, amino acid analysis is used to detect metabolic disorders. For example, amino acid analysis is used in the detection of phenylketonuria (PKU) in newborns and in following the metabolic state and dietary compliance of PKU patients.
Accordingly, there is a high demand for rapid, sensitive, and inexpensive methods for amino acid analysis. Unfortunately, current methods for amino acid analysis and protein end group analysis remain labor-intensive, slow, complicated, inaccurate, and insensitive. Historically, the determination of amino acids in protein hydrolysates and other samples has proven to be a difficult problem. The current art employs chromatography methods to separate the amino acids. Various chromatographic and electrophoretic techniques have been developed to resolve amino acids, including gas chromatography, reverse-phase chromatography with precolumn derivatization with various reagents, and ion exchange chromatography with postcolumn derivatization and capillary electrophoresis. These methods are complicated because the 20 primary amino acids do not differ from one another in any systematic way that is conducive to this analysis. Therefore, the separation of these 20 components is difficult. The task is further complicated by the similar structures and properties of many of the amino acids such as leucine, isoleucine, serine, and threonine, or tyrosine and phenylalanine. This method of analysis is further hindered by the sample composition. Samples are often a complex mixture of different substances such as proteins, carbohydrates, lipids, etc. The presence of these compounds interferes with the analysis, since they may bind to the stationary phase during chromatography, thereby limiting the capacity or blocking the column. In addition, most amino acids lack a strong chromophore for detection; hence amino acids need to be derivatized for detection. All of this translates into slow, tedious, expensive and inaccurate analysis.
The classical amino acid analyzers employ ion exchange chromatography to separate the amino acids followed by postcolumn reaction with ninhydrin. These complicated instruments, still in common use, are relatively insensitive (commonly nanomole detection, with lower limits of 200 to 500 picomoles of amino acids), slow, expensive and require an inordinate amount of time and effort to process a single sample. An additional complication is the relative instability of the ninhydrin reagent. “Within-run” and “between-run” precisions are often poor for an automated instrument. Additionally, these systems require relatively large amounts of sample for analysis. For example, they can require as much as 1 microgram of protein. This requirement can be problematic in analyzing very small amounts of sample material.
The current art for amino acid analysis and protein end group analysis also presents major obstacles for the production of protein and polypeptide based products, bioresearch, and proteome projects. Viability of techniques for amino acid analysis are driven increasingly by the needs for greater sensitivity, higher throughput, and lower costs. The more important amino acid identification becomes the more the inadequate the existing methodology
In short, the prior art techniques do not provide the rapid precise analysis required in today's environment, given the increased importance and demand for amino acid analysis. Therefore, a new approach to amino acid analysis is needed that is simple, rapid, sensitive, inexpensive and easy to use. Furthermore, methods and systems are needed that are suitable for miniaturization and multiplexing for the analysis of multiple samples in parallel. In addition, a need exists for real-time amino acid analyzers that can monitor amino acids in situ or in process control situations where samples are run periodically and results are desired quickly. Amino acids have important roles in metabolism and it is desirable to be able to analyze amino acids in vivo and in situ (e.g., in organisms and cell cultures)
At the molecular level, essentially all biological functions are mediated through the selective binding of ligands and receptors. In the past few decades, devices and systems applying “biomolecular recognition” phenomena for the analysis of samples used in diagnostics, research, therapeutics, and various monitoring processes have been developed.
This technique utilizes aspects of biological molecules at a molecular level. The identification of the sites and action of ligand-receptor interactions is essential for a molecular understanding of biology and pathology and for the development of novel therapeutics and other products including anti-microbial agents and pesticides. For example, enzymes, antibodies, receptors and nucleic acids respectively bind their substrates, antigens, ligands or complimentary strands with high specificity in the presence of thousands of other biomolecules. This specific binding is referred to as “biomolecular recognition”. For example, antibodies may recognize a single amino acid change in a protein. Likewise, enzymes specifically bind substrates in the presence of a multitude of molecules having similar structures, even when these other molecules are present in higher concentrations. For example, the accuracy of protein synthesis is insured by the specificity of a family of enzymes, called aminoacyl-tRNA synthetases. These enzymes act to charge tRNAs with their cognate amino acids.
New technologies are revolutionizing genomic research. For example, on-line microfluidic systems have been described for high-throughput DNA genotyping (Zhang et al, (1999) Anal Chem 71: 1138-45), polymerase chain reactions, and DNA sequencing reactions (Wooley et al. (1996) Anal. Chem. 68: 720-723). Results from massively parallel and quantitative gene expression measurements analyzing up to 40,000 genes at a time and whole-genome variant detection methods show the power and accuracy of combining biorecognition phenomena with miniaturized array based methods (Lipshutz, et al. (1999) Nat. Genet. 21: 20-24). Microarrays detect gene expression levels in parallel by measuring the hybridization of mRNA to many thousands of genes immobilized at high spatial resolution on a surface (Reviewed in Watson et al. (1998) Curr. Opin. Biotech. 9:609-614). Highly resolved detection is generally achieved by the laser induced fluorescence of a labeled probe. Capillary array electrophoresis, where many capillaries are run and detected in parallel, has recently been developed for rapid DNA sequencing (reviewed in Kheterpal and Mathies (1999) Anal. Chem. 71:31A-37A).
Unfortunately, recent advances in rapid micro gene analysis have not been duplicated for protein or polypeptide analysis or for amino acid analysis. This lack of development is unfortunate because, as stated above, protein and polypeptide amino acid compositional and amino acid sequence analysis are pivotal to biological research and the applications for amino acid analysis are vast. Thus, there is a long-felt need for new means of amino acid analysis which is simpler, faster, and cheaper.
N- and C-terminal amino acid sequence information can be used to verify start and stop points of protein coding sequences, to identify proteins and to identify proteolytic degradation products. Terminal sequences as short as four or five amino acid can often be useful in designed oligonucleotides for polymerase chain reaction or hybridization analyses.
Using carboxypeptidases and aminopeptidases along with amino acid analysis for protein end group sequencing is known. Over the years, these enzymes have been used in discontinuous kinetic assays for protein end group sequencing. Proteins are typically digested by these enzymes and samples of the digests are taken at various time points and analyzed later using an amino acid analyzer. However, due to the nonlinear rate of hydrolysis by these enzymes, kinetic assays have been unsuccessful in most cases. When an analyte varies rapidly and unpredictably, as in the case here, a continuous (real time) assay is needed. However, no continuous amino acid analyzers exist.
Further, automated methods are not presently available for identifying C-terminal sequences of proteins. C-terminal sequence tags are more specific than N-terminal sequence tags of the same length, but no reliable, sensitive method for C-terminal protein sequencing is currently available. Accordingly, new rapid methods for amino acid analysis and end-group protein sequencing are needed.
It would be advantageous to have a real time amino acid analyzer which could be used with exopeptidases, enzymes that remove amino acids sequentially (i.e., one at a time) from a protein's N- or C-terminus, to create integrated protein end group sequenators which microsystems would be suitable for generating either N- or C-terminal sequence tags from intact proteins or peptides on a microscale.
It would further be advantageous to have a method which alleviates at least some of the bottlenecks associated with drug discovery and large scale proteome projects created by the inadequacies in the current methods of amino acid analysis and allows rare proteins and peptides that can be isolated only in minute amounts to be analyzed for amino acid composition. Further, it would be advantageous to have a method, which requires only a tiny amount of sample for each measurement, shorter analysis time, and in situ and real time analyses. Further, it would be advantageous to have a system, which could be mass-produced at lower costs, thus enabling disposable, inexpensive amino acid analysis. Further, it would be advantageous to have a system for the simultaneous analysis of many samples and achieve greater sensitivity. Quite surprisingly, the present invention fulfills these and other needs.